Evaluating Productivity Management of Materials Handling System at Mempeasem Gold Mine

##plugins.themes.bootstrap3.article.main##

  •   Desmond B. Munyadzwe

  •   Nonduduzo B. Mamba

  •   Raymond Sogna Suglo

Abstract

Productivity management in materials handling is critical to mining operations. Most open pit mines use modular dispatch systems to control and monitor the movement of their materials handling equipment and operations. Statistical methods can be used on the data collected by the dispatch systems to identify major losses in time, tonnage and finances in productivity management. In this study, three ranking methods (a base case and two modified ranking methods) were used to evaluate the significance of the deviation and correlation parameters in productivity losses. A load and haul productivity loss ranking model was developed using data obtained from Mempeasem Gold Mine’s from January to October 2018 and tested with data obtained in November 2018. The results show that the ranking model can be used in the analysis of production data over any period of time and that the model is applicable in the analysis of the performance of all types of discrete load and haul equipment (trucks and excavators), either operating individually or in combination. The ranking based on deviation values is useful for comparative purposes. However, the ranking based on reduced values is more useful in decision making processes as it enables mine operators to take mitigation measures according to the level of priority of each item. Decision makers could also use the suggested colour coding for easy identification of the priority losses.


Keywords: Modular Dispatch System, Open Pit Mine, Productivity Management, Ranking Model

References

P. Mitchell, and J. Steen, Productivity in Mining; A Case for Broad Transformation, Melbourne: EYGM Limited, pp. 2-6, 2017.

S. Elevli, and B. Elevli, "Performance Measurement of Mining Equipment by Utilising OEE," Alcta Montanistica Slovaca, vol. 2, pp. 95-101, 2010.

H. Fourie, "Improvement in the Overall Efficiency of Mining Equipment: A Case Study", The Journal of Southern African Institute of Mining and Metallurgy, vol. 116, pp. 271-281, 2016.

Anglo-American Operating Model, Debswana Diamond Company, Gaborone, BW, 2018.

K. Gabanakgosi, K. Mosebi, O. Mogorosi, M. Barei K. Ntlotlang, and T. Thokweng, "A Multi-Disciplinary Approach to Dip Slope Mining in Jwaneng Mine, Botswana", Jwaneng Mine, Debswana Diamond Company, pp. 2-8, 2017.

V. Topp, L. Soames, D. Parham, and H. Bloch, Productivity in the Mining Industry: Measurement and Interpretation, Melbourne: Australian Government Productivity Commission, pp. 10-16, 2008.

G. Lumley, Mining for Efficiency, Melbourne: Pricewaterhouse Coopers, pp. 4-8, 2014.

A. Lala, M. Moyo, S. Rehbach, and R. Sellschop, Productivity at the Mine Face: Pointing the Way Forward, New York: McKinsey and Company, pp. 2-12, 2016.

P. Klein, Tracking the Trends 2018: The Top 10 Issues Shaping Mining in the Year Ahead, Melbourne: Deloitte, pp. 17, 2018.

P. Mitchell, L. Downham, and A. van Dinter. (November 2019). Top 10 business risks and opportunities – 2020. EYGM Limited. [Online]. Available: http://www.ey.com/en_gl/mining-metals/10-business-risks-facing-mining-and-metals.

S. C. Kundu. (March 2019). Post: What is the difference between data and information. ResearchGate. [Online]. Available: http://www.researchgate.net/post/What_is_the _difference _between_data_and_information.

Downloads

Download data is not yet available.

##plugins.themes.bootstrap3.article.details##

How to Cite
[1]
Munyadzwe, D., Mamba, N. and Suglo, R. 2020. Evaluating Productivity Management of Materials Handling System at Mempeasem Gold Mine. European Journal of Engineering and Technology Research. 5, 8 (Aug. 2020), 948-954. DOI:https://doi.org/10.24018/ejers.2020.5.8.1991.